On Wed, 2 Jul 2008, rlearner309 wrote:
>> I think the covariance between dummy variables or between dummy variables and
> intercept should always be zero. meaning: no sigularity problem??
>
No. You can easily check that this is not true using the cov() function. Indicator variables for mutually exclusive groups are negatively correlated.
-thomas
>> rlearner309 wrote:
>>>> This is actually more like a Statistics problem:
>> I have a dataset with two dummy variables controlling three levels. The
>> problem is, one level does not have many observations compared with other
>> two levels (a couple of data points compared with 1000+ points on other
>> levels). When I run the regression, the result is bad. I have unbalanced
>> SE and VIF. Does this kind of problem also belong to "near sigularity"
>> problem? Does it make any difference if I code the level that lacks data
>> (0,0) in stead of (0,1)?
>>>> thanks a lot!
>>>> --
> View this message in context: http://www.nabble.com/A-regression-problem-using-dummy-variables-tp18214377p18237666.html> Sent from the R help mailing list archive at Nabble.com.
>> ______________________________________________
>R-help at r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
>
Thomas Lumley Assoc. Professor, Biostatistics
tlumley at u.washington.edu University of Washington, Seattle